PyFAI, a versatile library for azimuthal regrouping

Abstract

2D area detectors like ccd or pixel detectors have become popular in the last 15 years for diffraction experiments (e.g. for waxs, saxs, single crystal and powder diffraction (xrpd)). These detectors have a large sensitive area of millions of pixels with high spatial resolution. The software package pyFAI has been designed to reduce saxs, waxs and xrpd images taken with those detectors into 1D curves (azimuthal integration) usable by other software for in-depth analysis such as Rietveld refinement, or 2D images (a radial transformation named caking). As a library, the aim of pyFAI is to be integrated into other tools like PyMca or edna with a clean pythonic interface. However pyFAI features also command line tools for batch processing, converting data into q-space (q being the momentum transfer) or 2θ-space (θ being the Bragg angle) and a calibration graphical interface for optimizing the geometry of the experiment using the Debye-Scherrer rings of a reference sample. PyFAI shares the geometry definition of spd but can directly import geometries determined by the software fit2d. PyFAI has been designed to work with any kind of detector and geometry (transmission or reflection) and relies on FabIO, a library able to read more than 20 image formats produced by detectors from 12 different manufacturers. During the transformation from cartesian space (x, y) to polar space (2θ, χ), both local and total intensities are conserved in order to obtain accurate quantitative results. Technical details on how this integration is implemented and how it has been ported to native code and parallelized on graphic cards are discussed in this paper.

Everything SAXS: small-angle scattering pattern collection and correction

“…In reality, however, the user can be left to their own devices and an idea on the required steps and sequence may be of some help. Several data processing packages are available to aid the user with the most pressing data correction steps [13,80,95,93] (not an exhaustive list).…”

“…[185]), one good way of dealing with these corrections is to determine a coordinate look-up table ('displacement maps') for each pixel. These maps can subsequently be used during the data averaging procedure (see section 3.4.10) to put the detected datapoints in the right bins [92,93].…”

Characterization of Gas‐Solid Reactions using In Situ Powder X‐ray Diffraction

“…using software like Fit2D or PyFAI. [27][28][29] Alternatively, intense and unwanted diffraction may also be masked by placing lead in front of the detector. These programs are used to convert the area detector frames (image files, binary format) to powder diffraction patterns, I(2θ) (ASCII format).…”

FabIO: easy access to two-dimensional X-ray detector images in Python

“…The code base was initiated by merging parts of our Fabian image viewer (Sørensen & Knudsen, 2006) and ImageD11 (Wright, 2005) peak-search programs and has been developed since 2007 as part of the TotalCryst (Poulsen et al, 2006) program suite for analysis of three-dimensional X-ray diffraction microscopy data (Sørensen et al, 2012). During integration into a range of scientific programs such as the Fable graphical interface (Gö tz et al, 2007), EDNA (Incardona et al, 2009) and the fast azimuthal integration library pyFAI (Kieffer & Karkoulis, 2013), FabIO has gained several features, including the ability to handle multi-frame image formats as well as to write many of the file formats.…”